ABSTRACT
This study explores how start-ups manage high-turbulent markets during the first six-months of the COVID-19 pandemic, and how dynamic capabilities are operationalized in that situation. A multiple-case study approach was employed to investigate eight start-up cases in Indonesia. Indonesia was chosen to represent an emerging economy with a tremendous growing number of start-ups. The data are presented based on the evolving circumstances of the COVID-19 crisis. The research findings illustrate how dynamic capabilities are operationalized simultaneously with the validation of adjusted business models through simple-experiential routines, iterative executions, and action-oriented processes amidst the high-turbulent markets. Dynamic capabilities that operate in full combination by sensing, seizing, and transforming capabilities potentially can facilitate the creation of values for firms faster than otherwise. This study also identifies specific elements and alignment mechanisms incorporated in the dynamic capabilities.
ABSTRACT
This paper discusses the structure of digital conversations about Covid-19 on Twitter. Social network analysis was adopted to examine the relationship structure amongst Twitter users engaged within the network of conversations, and what kind of content users communicate with each other. We collected 97.067 tweets since March 2020 until April 2021, then analyzed the tweet conversations using NodeXL software. The results show that the network of conversations was a low-density network with a low reciprocity vertex pairs ratio. This suggests that the conversations were not effectively built. The top-ten most popular actors engaged in the conversations were dominated by government institution accounts. There were also many mentions to popular accounts. However, popular actors did not actively respond to the conversations that ensued. These findings emphasize that during the global health crisis, which was characterized by uncertain situations, people were inclined to search for related information on a daily basis from authorities. Some users also mentioned suggestions to the authorities to share official information related to the constantly changing situations. This study also highlighted that Twitter was able to facilitate important conversations, because of its capability to distribute information widely and quickly. © 2023 IEEE.
ABSTRACT
Purpose: The COVID-19 pandemic has significantly affected how consumers make payment choices. This study aims to develop a comprehensive model explaining customers’ continuance usage of mobile payment during the COVID-19 pandemic by investigating both the pull (positive) factors of mobile payment and the push (negative) factors of cash payment. Design/methodology/approach: A survey was conducted on 508 mobile payment users. A quota sampling method was applied to collect the data. Then, the data were analyzed using structural equation modeling. This study employed SPSS and LISREL software. Findings: This study reveals that four antecedent factors: favorable attitude toward mobile payment, social influence, facilitating conditions and unfavorable attitude toward cash payment, positively affect the continuance intention to use mobile payment during the COVID-19 pandemic. The finding also corroborates the effect of continuance intention on the actual use of mobile payment. Practical implications: This research provides valuable insights for formulating business strategies. The results indicate that mobile payment providers should not only consider the positive aspects of mobile payments but also the negative aspects of cash payment when encouraging the continuance usage of mobile payments to customers. Originality/value: This study is among the first to empirically test the effect of unfavorable attitudes toward cash payment on the continuing use of mobile payment. Specifically, the research extends the unified theory of acceptance and use of technology by adding the push–pull-mooring model to enhance the explanatory power. © 2022, Istijanto and Indria Handoko.
ABSTRACT
Twitter becomes one of the most adopted social media platforms globally, and Indonesia is a country with a rapid growth of Twitter user number in recent years. This paper discusses about the examination of conversation network of Twitter hashtag related to Covid-19 in Indonesia by using a network perspective. During this pandemic situation, Twitter has been increasingly adopted as a medium of conversational interaction amongst people to express their opinion and feeling about the situation, or share information, among others. At the same time, the Indonesian Government has established an official hashtag (#) to coordinate and organize conversations related to a specific topic of Covid-19, namely #BersatuLawanCovid19. In this way, the Government would be able to reach the public interest due to the capability of the hashtag to become a trending topic. This study examines how the Twitter conversations emerged and developed within the Twitter community by using Social Network Analysis approach. We have collected 793 Twitter users and 4441 Twitter chats from the hashtag #BersatuLawanCovid19. We then visualized the relationship network and examined the community using Social Network Analysis metrics with NodeXL. This study found that there is no a mutual engagement amongst the community members in terms of conversational practices. Interestingly, although some members of the community received a high number of engagement efforts from others, they do not actively respond to the initiatives. This suggests that the official account of government who is in-charge of managing the conversation need to enhance their communication strategy to improve the conversation within the community.